{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Subgraph as compiled graph sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "var userHomeDir = System.getProperty(\"user.home\");\n",
    "var localRespoUrl = \"file://\" + userHomeDir + \"/.m2/repository/\";\n",
    "var langchain4jVersion = \"0.36.2\";\n",
    "var langgraph4jVersion = \"1.4-SNAPSHOT\";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%bash \n",
    "rm -rf \\{userHomeDir}/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/bsc/langgraph4j"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mRepository \u001b[1m\u001b[32mlocal\u001b[0m url: \u001b[1m\u001b[32mfile:///Users/bsorrentino/.m2/repository/\u001b[0m added.\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32morg.slf4j:slf4j-jdk14:2.0.9\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32morg.bsc.langgraph4j:langgraph4j-core:1.4-SNAPSHOT\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32morg.bsc.langgraph4j:langgraph4j-langchain4j:1.4-SNAPSHOT\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32mdev.langchain4j:langchain4j:0.36.2\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32mdev.langchain4j:langchain4j-open-ai:0.36.2\n",
      "\u001b[0mAdding dependency \u001b[0m\u001b[1m\u001b[32mnet.sourceforge.plantuml:plantuml-mit:1.2024.8\n",
      "\u001b[0mSolving dependencies\n",
      "Resolved artifacts count: 27\n",
      "Add to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/slf4j/slf4j-jdk14/2.0.9/slf4j-jdk14-2.0.9.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/slf4j/slf4j-api/2.0.9/slf4j-api-2.0.9.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/bsc/langgraph4j/langgraph4j-core/1.4-SNAPSHOT/langgraph4j-core-1.4-SNAPSHOT.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/bsc/async/async-generator/3.0.0/async-generator-3.0.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/bsc/langgraph4j/langgraph4j-langchain4j/1.4-SNAPSHOT/langgraph4j-langchain4j-1.4-SNAPSHOT.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/dev/langchain4j/langchain4j/0.36.2/langchain4j-0.36.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/dev/langchain4j/langchain4j-core/0.36.2/langchain4j-core-0.36.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/google/code/gson/gson/2.10.1/gson-2.10.1.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/apache/opennlp/opennlp-tools/1.9.4/opennlp-tools-1.9.4.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/dev/langchain4j/langchain4j-open-ai/0.36.2/langchain4j-open-ai-0.36.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/dev/ai4j/openai4j/0.23.0/openai4j-0.23.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/retrofit2/retrofit/2.9.0/retrofit-2.9.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/retrofit2/converter-jackson/2.9.0/converter-jackson-2.9.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/fasterxml/jackson/core/jackson-databind/2.17.2/jackson-databind-2.17.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/fasterxml/jackson/core/jackson-annotations/2.17.2/jackson-annotations-2.17.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/fasterxml/jackson/core/jackson-core/2.17.2/jackson-core-2.17.2.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/okhttp3/okhttp/4.12.0/okhttp-4.12.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/okio/okio/3.6.0/okio-3.6.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/okio/okio-jvm/3.6.0/okio-jvm-3.6.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/jetbrains/kotlin/kotlin-stdlib-common/1.9.10/kotlin-stdlib-common-1.9.10.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/squareup/okhttp3/okhttp-sse/4.12.0/okhttp-sse-4.12.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/jetbrains/kotlin/kotlin-stdlib-jdk8/1.9.25/kotlin-stdlib-jdk8-1.9.25.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/jetbrains/kotlin/kotlin-stdlib/1.9.25/kotlin-stdlib-1.9.25.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/jetbrains/annotations/13.0/annotations-13.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/org/jetbrains/kotlin/kotlin-stdlib-jdk7/1.9.25/kotlin-stdlib-jdk7-1.9.25.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/com/knuddels/jtokkit/1.1.0/jtokkit-1.1.0.jar\u001b[0m\n",
      "\u001b[0mAdd to classpath: \u001b[0m\u001b[32m/Users/bsorrentino/Library/Jupyter/kernels/rapaio-jupyter-kernel/mima_cache/net/sourceforge/plantuml/plantuml-mit/1.2024.8/plantuml-mit-1.2024.8.jar\u001b[0m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "%dependency /add-repo local \\{localRespoUrl} release|never snapshot|always\n",
    "// %dependency /list-repos\n",
    "%dependency /add org.slf4j:slf4j-jdk14:2.0.9\n",
    "%dependency /add org.bsc.langgraph4j:langgraph4j-core:\\{langgraph4jVersion}\n",
    "%dependency /add org.bsc.langgraph4j:langgraph4j-langchain4j:\\{langgraph4jVersion}\n",
    "%dependency /add dev.langchain4j:langchain4j:\\{langchain4jVersion}\n",
    "%dependency /add dev.langchain4j:langchain4j-open-ai:\\{langchain4jVersion}\n",
    "%dependency /add net.sourceforge.plantuml:plantuml-mit:1.2024.8\n",
    "\n",
    "%dependency /resolve"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**utility to render graph respresentation in PlantUML**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import net.sourceforge.plantuml.SourceStringReader;\n",
    "import net.sourceforge.plantuml.FileFormatOption;\n",
    "import net.sourceforge.plantuml.FileFormat;\n",
    "import org.bsc.langgraph4j.GraphRepresentation;\n",
    "\n",
    "void displayDiagram( GraphRepresentation representation ) throws IOException { \n",
    "    \n",
    "    var reader = new SourceStringReader(representation.getContent());\n",
    "\n",
    "    try(var imageOutStream = new java.io.ByteArrayOutputStream()) {\n",
    "\n",
    "        var description = reader.outputImage( imageOutStream, 0, new FileFormatOption(FileFormat.PNG));\n",
    "\n",
    "        var imageInStream = new java.io.ByteArrayInputStream(  imageOutStream.toByteArray() );\n",
    "\n",
    "        var image = javax.imageio.ImageIO.read( imageInStream );\n",
    "\n",
    "        display(  image );\n",
    "\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Graph State**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.bsc.langgraph4j.prebuilt.MessagesState;\n",
    "import org.bsc.langgraph4j.state.Channel;\n",
    "import org.bsc.langgraph4j.state.AppenderChannel;\n",
    "\n",
    "public class State extends MessagesState<String> {\n",
    "\n",
    "    public State(Map<String, Object> initData) {\n",
    "        super( initData  );\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Utility action to simplify node creation**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.bsc.langgraph4j.action.AsyncNodeAction;\n",
    "\n",
    "AsyncNodeAction<State> makeNode( String id ) {\n",
    "    return node_async(state ->\n",
    "            Map.of(\"messages\", id)\n",
    "    );\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a subgraph as compiled graph**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.bsc.langgraph4j.StateGraph;\n",
    "import org.bsc.langgraph4j.action.AsyncNodeAction;\n",
    "import static org.bsc.langgraph4j.action.AsyncNodeAction.node_async;\n",
    "import static org.bsc.langgraph4j.action.AsyncEdgeAction.edge_async;\n",
    "import static org.bsc.langgraph4j.StateGraph.END;\n",
    "import static org.bsc.langgraph4j.StateGraph.START;\n",
    "\n",
    "var workflowChild = new StateGraph<>(State.SCHEMA, State::new)        \n",
    "                    .addNode(\"child:step_1\", makeNode(\"child:step1\") )\n",
    "                    .addNode(\"child:step_2\", makeNode(\"child:step2\"))\n",
    "                    .addNode(\"child:step_3\", makeNode(\"child:step3\"))\n",
    "                    .addEdge(START, \"child:step_1\")\n",
    "                    .addEdge(\"child:step_1\", \"child:step_2\")\n",
    "                    .addConditionalEdges(  \"child:step_2\",\n",
    "                                edge_async(state -> \"continue\"),\n",
    "                                Map.of( END, END, \"continue\", \"child:step_3\") )\n",
    "                    .addEdge(\"child:step_3\", END)\n",
    "                    ;\n",
    "var compiledWorkflowChild = workflowChild.compile();\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create graph with a sub graph as compiled graph**\n",
    "> The subgraph will be executed independently to the parent sharing its state but not `CompileConfig`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NodeOutput{node=__START__, state={messages=[]}}\n",
      "NodeOutput{node=step_1, state={messages=[step1]}}\n",
      "NodeOutput{node=step_2, state={messages=[step1, step2]}}\n",
      "NodeOutput{node=__START__, state={messages=[step1, step2]}}\n",
      "NodeOutput{node=child:step_1, state={messages=[step1, step2, child:step1]}}\n",
      "NodeOutput{node=child:step_2, state={messages=[step1, step2, child:step1, child:step2]}}\n",
      "NodeOutput{node=child:step_3, state={messages=[step1, step2, child:step1, child:step2, child:step3]}}\n",
      "NodeOutput{node=__END__, state={messages=[step1, step2, child:step1, child:step2, child:step3]}}\n",
      "NodeOutput{node=subgraph, state={messages=[step1, step2, child:step1, child:step2, child:step3]}}\n",
      "NodeOutput{node=step_3, state={messages=[step1, step2, child:step1, child:step2, child:step3, step3]}}\n",
      "NodeOutput{node=__END__, state={messages=[step1, step2, child:step1, child:step2, child:step3, step3]}}\n"
     ]
    }
   ],
   "source": [
    "\n",
    "var workflow = new StateGraph<>(State.SCHEMA, State::new)        \n",
    "                    .addNode(\"step_1\",  makeNode(\"step1\"))\n",
    "                    .addNode(\"step_2\",  makeNode(\"step2\"))\n",
    "                    .addNode(\"step_3\",  makeNode(\"step3\"))\n",
    "                    .addSubgraph( \"subgraph\", compiledWorkflowChild )\n",
    "                    .addEdge(START, \"step_1\")\n",
    "                    .addEdge(\"step_1\", \"step_2\")\n",
    "                    .addEdge(\"step_2\", \"subgraph\")\n",
    "                    .addEdge(\"subgraph\", \"step_3\")\n",
    "                    .addEdge(\"step_3\", END)\n",
    "                    ;\n",
    "\n",
    "var compiledWorkflow = workflow.compile();\n",
    "\n",
    "for( var step : compiledWorkflow.stream( Map.of() )) {\n",
    "    System.out.println( step );\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Display StateGraph** as you defined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var representation = compiledWorkflow.getGraph( GraphRepresentation.Type.PLANTUML, \"sub graph\", false );\n",
    "\n",
    "displayDiagram( representation );"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Display Compiled Graph result as graph processing**\n",
    "> in such case the result will be the same of previous one because no merge will be done"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var representation = compiledWorkflow.getGraph( GraphRepresentation.Type.PLANTUML, \"merged sub graph\", false );\n",
    "\n",
    "displayDiagram( representation );"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Java (rjk 2.2.0)",
   "language": "java",
   "name": "rapaio-jupyter-kernel"
  },
  "language_info": {
   "codemirror_mode": "java",
   "file_extension": ".jshell",
   "mimetype": "text/x-java-source",
   "name": "java",
   "nbconvert_exporter": "script",
   "pygments_lexer": "java",
   "version": "17.0.2+8-86"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
